How to Build Vision Data Agents with Tools, Skills, and MCP - October 29, 2026
An online workshop on building agents that act on visual datasets through tools, reusable skills and MCP. Examples cover tagging, inference, evaluation and workflow integration, alongside design patterns for reliable agent systems.
When
Oct 29, 2026
Where
Online event
Attendance
Virtual
Status
scheduled
Event type
Workshop · Published by organizer
Registration
See the organizer for current access, pricing and registration details.
Workshop · Editorial classification · Oct 29, 2026
AI agents are rapidly changing how teams build and scale machine learning workflows—but most implementations still rely on fragmented tools, manual processes, and brittle integrations.
In this session, you’ll learn how to build production-ready AI agents that can reason over your data, automate complex tasks, and integrate seamlessly into your existing stack using tools, skills, and the Model Context Protocol (MCP).
We’ll walk through how modern agentic systems move beyond simple prompts—leveraging structured tools like dataset operations, embeddings, evaluation pipelines, and model execution to take real action. You’ll see how these agents can tag data, run inference, evaluate performance, and surface insights automatically, all within a unified workflow.
By combining natural language interfaces with programmable building blocks, teams can dramatically reduce manual effort, accelerate experimentation, and unlock faster decision-making across the ML lifecycle.
Whether you're building data-centric AI systems, managing large-scale vision datasets, or exploring agentic workflows for the first time, this session will give you a practical blueprint for getting started.
What you’ll learn:
How AI agents actually work in production: Move beyond hype—understand how agents use tools, memory, and structured workflows to execute real tasksUsing tools to take action on your data: Program agents to run operations like filtering labels, computing embeddings, evaluating detections, and moreWhat “skills” are and how they enable multi-step workflows: Learn how to package complex logic into reusable capabilities your agents can call on demandHow MCP connects your models, tools, and agents: See how MCP standardizes communication between LLMs and external systems for scalable, flexible architecturesAutomating the ML lifecycle with agents: From data curation to model evaluation, discover how to eliminate repetitive workflows and accelerate iterationBest practices for building reliable agentic systems: Design patterns, guardrails, and practical tips for deploying agents in real-world environments
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agenda
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Published schedule: 9:00 AM - 10:00 AM PST. Exact time and timezone withheld because organizer abbreviations are not independently reconciled. Full biographies/abstracts retained in immutable HTML receipt. Sponsor, exhibitor and attendee lists not inferred from speaker employers. Session local day: the published single-day event page groups these agenda items/talks on 2026-10-29. Exact times remain unknown where timezone labels are unresolved.